Sentiment OAuth App

A web-based sentiment analysis application created as part of a learning course in machine learning and web development.
The project integrates front-end UI development with modern authentication, deployment, and application structure practices.

🎯 Project Purpose

This app was developed as a course project to practice and demonstrate key concepts such as:

• OAuth authentication (GitHub login)
• Sentiment analysis in the UI
• Secure session handling with localStorage
• Frontend and backend integration
• Docker & GitHub Actions-based deployment to Azure

🔧 Features

• 🔐 GitHub OAuth login (with session checks)
• 💬 Sentiment analysis input/output
• 💄 Accessible and responsive HTML interface
• 🐳 Docker + Docker Compose setup
• 🚀 CI/CD deployment via GitHub Actions to Azure
• 🗂 Login/register system with hashed passwords

🧠 Topics Covered

• Web development (HTML, JS, login systems)
• RESTful integration and session management
• DevOps tools: Docker, GitHub Actions, Azure App Service
• Basic machine learning application in UI (sentiment prediction)
• Frontend/backend connection with secure flow

🚀 Getting Started

Requirements

• GitHub OAuth App credentials
• Docker and Docker Compose
• Azure App Service account (optional)

Run Locally

git clone https://github.com/your-username/sentiment-oauth-app.git
docker-compose up --build